Presentation by Carlianne PATRICK, Associate Professor Georgia State University (US) at the 10th Spatial Productivity Lab meeting of the OECD Trento Centre, co-organised with Swedish Entrepreneurship Forum, held in virtual format on 29 October 2020. More OECD info: https://oe.cd/SPL More Swedish Entrepreneurship Forum info: https://entreprenorskapsforum.se/en/

1. CARLIANNE PATRICK
Associate Professor, Georgia State University (US)
Effects of economic incentives on business start-ups
in the US: County-level evidence
29 October 2020 | 15.30-17.00 CET | WebinarBusiness incentives and firm entry: The past, the present and the future
Mark Partridge1,2,3
Alexandra Tsvetkova4
Sydney Schreiner1
Carlianne Patrick5
1The Ohio State University;
2Jinan University;
3Urban Studies and Regional Science, Gran Sasso Science Institute;
4OECD, Trento Italy
5Georgia State University

2. Focus on incentives and start-ups: Why?
• Start-ups are central drivers of regional economic growth (job creation, larger
multipliers, particularly large effects in lagging regions)  policy support
• State and local business incentives are on the rise and cost a lot (2015
estimate = USD 45 billion); they often aim to stimulate entry overall or in
specific sectors
• Evidence on incentives effectiveness is mixed
• Incentives may have unintended consequences (capital-labor substitution,
upward pressure on input prices, crowding out, disproportional benefits to
larger firms at the expense of start-ups/smaller firms, etc.)
Effectiveness of business incentives at regional level is unclear
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3. Our study: Two research questions
1. What are the effects of state economic incentives on business
entry in US counties?
2. How do effects differ (if at all) by types by sectors/industries?
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4. Empirical approach
• Timeframe: 2001-2013
• Sample: 246 counties across 33 metro areas
• The 47 metro areas are the largest in their states (with a couple of exceptions)
• The 33 states represent 92% of US GDP
• Estimation approach: Lewbel (2012) IV, IV, LIML IV, Negative Binomial
and OLS
• Data sources:
• Dependent Variables (entries) – US Census BITS
• Incentives and taxes – W. E. Upjohn Institute
• Instrument (Incentive Environment Index) – Patrick, 2014 9

5. Estimated models
• 3-year differenced model (main specification):
• Instrument: 2000 Incentive Environment Index (IEI) by year/period dummy
interactions
• IEI measure constructed from from state constitutions (Patrick, 2014)
• How easy gov’ts can aid businesses
• From 19th century, county reverse causality minimized
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6. Additional control variables
• Industry mix demand shifter (Bartik instrument)
• 1990 education (% HS only; % some coll; % BA)
• 1990 log population
• 1990 industry structure (% labor-intensive manufacturing; total
manufacturing; agriculture, mining)
• Job flow
- a measure of industrial composition that is more or less likely to have
workers flow among sectors
• Year/period fixed effects
• State fixed effects
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7. Lewbel IV results for the 3-year differences in number of
establishment births per capita (logged)
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8. Lewbel IV results for the 3-year differences in the number
of establishment births per capita (logged)
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9. Conclusions
• Our results suggest that overall incentives have no or negative effect
on firm entry, either in the industry receiving the incentives, or overall
• Preferred Lewbel (2012) IV procedure, a one-standard deviation
change in total incentives is associated with a -0.13 standard deviation
change in total startups
• Incentives for export industries and for manufacturing in particular are
negatively associated with the change in total startups
• These findings suggest that incentives crowd out new firms, and the
crowding out effect is so large that it offsets any effect incentives might
have in attracting new firms
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10. Other considerations
• Local demand shocks and inter-sector job mobility are both positively
associated with higher total startups
• Greater sectoral job mobility is consistent with those who argue that non-
competes, NDAs, and occupational licensing damage economic
dynamism
• The results are robust across a variety of industries, as well as
regression and count data methods
• If incentives improve performance of firms that receive them and this
improved performance outweighs the crowding-out loss from the
incentives, these results are less discouraging
• Economic theory, however, and the existing evidence seem to suggest that this is
not likely to be the case
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11. THANK YOU!
Carlianne Elizabeth Patrick
cpatrick@gsu.edu
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